# Supertonic vs VoxCPM2 WER/CER: How the 99M Parameter Model Matches 2B Parameter Accuracy

> Discover how Supertonic's 99M parameter TTS model rivals VoxCPM2's 2B parameter accuracy in WER/CER. Get comparable or better results with fewer resources.

- Repository: [Supertone Inc./supertonic](https://github.com/supertone-inc/supertonic)
- Tags: performance
- Published: 2026-06-15

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**Supertonic achieves comparable or lower word error rates (WER) and character error rates (CER) than VoxCPM2 across the majority of benchmarked languages, despite using 20× fewer parameters (99M vs 2B) and running inference on CPU-only devices via ONNX Runtime.**

Supertonic is an open-weight text-to-speech (TTS) system developed by Supertone Inc. that prioritizes on-device deployment without sacrificing pronunciation quality. According to the `supertone-inc/supertonic` source code, the model was evaluated against VoxCPM2—a 2 billion parameter open-weight TTS model—using the MiniMax-MLS-test benchmark to measure transcription accuracy across 31 languages.

## Architectural Innovations in Supertonic

Supertonic’s efficiency stems from two core architectural contributions implemented in the ONNX Runtime inference pipeline.

### Length-Aware Rotary Position Embedding (LARoPE)

As documented in [`README.md`](https://github.com/supertone-inc/supertonic/blob/main/README.md), LARoPE improves text-speech alignment within cross-attention layers by incorporating positional information that adapts to sequence length. This mechanism ensures precise phoneme